The present invention relates generally the field of biometric identification and authentication, and more particularly to a multimodal biometric system and method.
Biometrics is a generic term for characteristics that can be used to distinguish one individual from another, particularly through the use of digital equipment. An example of a biometric is a fingerprint. Trained analysts have long been able to match fingerprints in order to identify individuals. More recently, computer systems have been developed to match fingerprints automatically. Examples of biometrics that have been, or are now being, used to identify, or authenticate the identity of, individuals include 2D face, 3D face, hand geometry, single fingerprint, ten finger live scan, iris, palm, full hand, signature, ear, finger vein, retina, DNA and voice. Other biometric may include characteristic gaits, lip movements and the like. New biometric are being developed or discovered continually.
Biometrics have been used both for identification and authentication. Identification is the process of identifying or detecting the presence of an unknown individual. Identification typically involves a one to N or complete search of stored biometric information. Common uses of identification are law enforcement facial mug shot or fingerprint searches, drivers license facial photo or fingerprint searches to ensure that a particular individual is not issued more than one drivers license, and various crowd scanning schemes to detect criminals or terrorists.
Authentication is the process of verifying that an individual is who he says he is. The individual presents something such as a card or computer logon name that identifies him. Then a biometric obtained from the individual is compared to a stored biometric to authenticate the individual's identity. Authentication is useful for controlling access to secure locations and systems and for controlling the uses of credit cards and the like.
In these days of heightened security, biometrics are becoming increasingly important. One of the goals in biometrics is increased accuracy so that there are fewer false negative and false positive indications. Every biometric has some limitations. Some biometrics are inherently more accurate than others. It is estimated that approximately 5% of the individuals in most populations do not have legible fingerprints. The accuracy of some face recognition systems may be dependent on ambient lighting and the pose of the subject.
A problem in current biometric identification and authentication is “spoofing” , which amounts to tricking the biometric capture device. Some devices may be spoofed by presenting a previously captured authentic image to the capture device. The device may capture the counterfeit image and then identify the wrong individual.
One solution both to the accuracy and spoofing concerns is to use multiple biometrics in identifying or authenticating the identity of an individual. For any single biometric, there is a finite probability that multiple individuals will match on that biometric. However, biometrics tend to be independent of each other so that it is unlikely that individuals that match on one biometric would match on multiple biometrics. Accordingly, the likelihood that an individual would score false positives on multiple biometric tests is low. In order to spoof a system that uses multiple biometrics, one would have to have to obtain counterfeit images for each biometric. Thus, there is a desire to provide multimodal biometric platforms. However, there are a number of problems with current attempts to provide a multimodal biometric platform.